Evidence map›Paper›PMID 40654502›Full record

ArticleJournal of mood and anxiety disorders2024

The relationship between risk perception, anxiety and paranoia - A predictive model in a community sample.

Suzanne H So, Anson Kai Chun Chau, Brandon A Gaudiano, Lyn Ellett, Tania M Lincoln, Eric M J Morris, Jessica L Kingston

Abstract read
In one paragraph

Article in Journal of mood and anxiety disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Suzanne H SoDepartment of Psychology, The Chinese University of Hong Kong, Hong Kong Special Administrative Region.
Anson Kai Chun ChauDepartment of Psychology, The Chinese University of Hong Kong, Hong Kong Special Administrative Region.
Brandon A GaudianoDepartment of Psychiatry and Human Behavior, Brown University, Providence, RI, USA.
Lyn EllettSchool of Psychology, University of Southampton, Southampton, UK.
Tania M LincolnDepartment of Clinical Psychology and Psychotherapy, University of Hamburg, Hamburg, Germany.
Eric M J MorrisSchool of Psychology and Public Health, La Trobe University, Melbourne, Australia.
Jessica L KingstonDepartment of Psychology, Royal Holloway, University of London, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Biases in risk perception (e.g. excessive attribution of likelihood of negative events happening to oneself, or perceived harm of neutral events) have been suggested as risk factors for psychopathologies such as generalised anxiety and persecutory ideation, although this line of research is limited by small samples and a lack of a suitable risk perception scale. Methods: Using the Risk Perception Questionnaire, four risk perception dimensions (likelihood, harm, controllability, and intentionality) of negative and neutral events were tested in association with anxiety and paranoia. In view of common co-occurrence between the two symptom variables, their associations with risk perception were tested by using partial correlations (at baseline) and comparisons of cross-lagged path models (over 3 months). Results: A representative community-based sample of 445 adults were included. At baseline, after controlling for correlations between levels of anxiety and paranoia, anxiety was uniquely correlated with three risk perception dimensions for negative events (likelihood, harm, and intentionality), whereas paranoia was uniquely correlated with all risk perception dimensions for both negative and neutral events. The best-fitted cross-lagged path model revealed that, after controlling for auto-regressions within variables, baseline level of anxiety predicted perceived harm of negative events at 3 months, whereas baseline levels of perceived intentionality of neutral events and likelihood of negative events predicted level of paranoia at 3 months. Conclusions: While risk perception of negative events is shared between anxiety and paranoia, risk perception of neutral events is uniquely characteristic of paranoia. Implications on maintenance of sub-clinical symptoms are discussed.

Indexed as

Paranoid ideationPersecutoryPsychosisTransdiagnosticWorry

Identifiers

PMID40654502
PMCPMC12243980

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.